The &#8216;cold, hard' numbers can lead to smarter decisions even as they promote the best of the 'warm and fuzzy' in company cultures.

That is, all signs point to much greater use in the near future of data analysis for people management. If it's done right, that's an exciting prospect for organizations and employees. The "cold, hard" numbers can lead to smarter decisions even as they promote the best of the "warm and fuzzy" in company cultures.

What do I mean about data analysis on the rise? Consider these recent developments:

Technology vendors continue to release analytic tools—such as SilkRoad technology's Point product that sifts through social networking activity to find nuggets like the employees whom top performers turn to for information.

I learned about the SilkRoad and Marsh examples at last week's IHRIM conference in Chicago. IHRIM—the International Association for Human Resource Information Management—is made up of people who might be termed the "propeller-heads" of human resources.

I say that with deep affection. I've been attending the annual IHRIM meetings for six years and many of the 700 or so people who come to these shows are the HR techies who slog away at making people management systems work more efficiently and effectively. Also at the shows are software vendors pitching products and consultants who aim to help firms install the tools.

To be sure, HR technology remains imperfect. Many companies are dissatisfied with the software tools they get and are far from sophisticated at number crunching related to their people. But I'm not the only one sensing the field is turning a corner.

Jac Fitz-enz, pretty much the father of workforce metrics, says he has seen a significant uptick in projects related to workforce analytics in just the past year. Among the companies "doing" workforce analytics, Fitz-enz says, are Alcoa Inc., Coca-Cola Co., Rio Tinto and Lowe's Cos. He's gratified by the recent momentum, especially given a lull during the depths of the recession. "I wasn't so sure a couple of years ago," Fitz-enz says after leading a session at the IHRIM show.

That session revealed some of the promise of workplace data. Fitz-enz' co-presenter, Jeff Higgins of consulting firm the Human Capital Management Institute, showed off some compelling metrics, such as the Workforce Image Map. This is a bar chart that breaks down employees in an organization by job function. Higgins compared two anonymous technology companies using this tool, and what screamed off the screen was the way one had loaded up on salespeople while skimping on R&D and customer service employees. The clear lesson: the sales-heavy firm ran a high risk of unsustainable growth.

Higgins is a numbers guy. Earlier in his career he was a chief financial officer. And he recounted that he routinely quashed proposals to invest in employees because HR officials didn't have return-on-investment figures or a business case based on numbers.

But that's changing. Newer tools and growing expertise in organizations around measuring people is making those calculations possible. One of the secrets, Higgins says, is that people-related metrics don't have to be perfect. Finance folks have always had imperfect numbers and made assumptions. "Their data was never clean," he says.

One of the fears of more metrics in HR is that they can be used as a weapon against workers. That's a real risk. Simplistic benchmarks and other figures can be used to justify morale-killing cuts. And sometimes data-driven layoffs are necessary for business survival.

But the surprising thing about workforce analytics is that they can refocus executives on winning over employees. As with the Workforce Image Map, smartly framed data that considers long-term growth tends to justify exactly the kinds of initiatives Higgins used to reject as CFO.

Things like training programs or recognition initiatives. Intuitively, Higgins knew these sorts of proposals made sense. And now CFOs have grounds to approve them. "This kind of analysis brings HR and finance together," he says.

Who would have thought numbers could get hard heads and soft hearts on the same page? But it's possible with big data. And this hopeful trend is only going to get bigger.